[{"collection_subject_count":124,"data_usage":"Secondary Analysis","description":"Lateralization is a fundamental principle of structural brain organization. In vivo imaging of brain asymmetry is essential for deciphering lateralized brain functions and their disruption in neurodevelopmental and neurodegenerative disorders. Here, we present a normative framework for benchmarking brain asymmetry across the lifespan, developed from an aggregated sample of 128 primary neuroimaging studies, including 177,701 scans from 138,231 individuals, jointly spanning the age range from 20 post menstrual weeks to 102 years. This resource includes comprehensive, hemisphere-specific brain growth charts for multiple neuroimaging phenotypes: regional cortical grey matter volume, thickness, surface area, and subcortical volumes. Our findings reveal distinct spatial patterns of asymmetry, with early leftward asymmetry observed in association cortices and late rightward asymmetry in sensory regions. These trajectories support theories of the neuroplasticity of asymmetry and the role of both genetic and environmental factors in shaping brain lateralization. Additionally, we provide tools to generate asymmetry centile scores, which allow the quantification of individual deviations from typical asymmetry throughout the lifespan and can be applied to unseen data or clinical populations. We demonstrate the utility of these models by highlighting group-level differences in asymmetry in autism spectrum disorder, schizophrenia, and Alzheimer’s disease, and exploring genetic correlations with hemispheric specialization. To facilitate further research, we have made this normative framework freely available as an interactive open-access resource (upon publication), offering an essential tool to advance both basic and clinical neuroscience.","doi":"10.15154/3er3-dc69","id":3066,"state":"Shared","study_subject_count":8552,"title":"Lifespan development of brain asymmetry"},{"collection_subject_count":76,"data_usage":"Secondary Analysis","description":"A major goal of precision medicine is to predict prognosis based on individualized information at the earliest possible points in development. Using early snapshots of adaptive functioning and unsupervised data- driven discovery methods, we uncover highly stable early autism subtypes that yield information relevant to later prognosis. Data from the National Institute of Mental Health Data Archive (NDA) (n = 1,098) was used to uncover three early subtypes (<72 months) that generalize with 96% accuracy. Outcome data from NDA (n = 2,561; mean age, 13 years) also reproducibly clusters into three subtypes with 99% generalization accuracy. Early snapshot subtypes predict developmental trajectories in non-verbal cognitive, language and motor domains and are predictive of membership in different adaptive functioning outcome subtypes. Robust and prognosis- relevant subtyping of autism based on early snapshots of adaptive functioning may aid future research work via prediction of these subtypes with our reproducible stratification model.","doi":"10.15154/0z1c-1d37","id":2396,"state":"Shared","study_subject_count":3517,"title":"Prognostic early snapshot stratification of autism based on adaptive functioning"},{"collection_subject_count":77,"data_usage":"Secondary Analysis","description":"Background: Autism spectrum disorder (ASD) is the second-most common neurodevelopmental disorder in childhood. This complex developmental disorder that manifests with restricted interests, repetitive behaviors, and difficulties in communication and social awareness. The inherited and acquired causes of ASD impact many and diverse brain regions, challenging efforts to identify a shared neuroanatomical substrate for this range of symptoms. The striatum and its connections are among the most implicated sites of abnormal structure and/or function in ASD. Striatal projection neurons develop in segregated tissue compartments, the matrix and striosome, that are histochemically, pharmacologically, and functionally distinct. Immunohistochemical assessment of ASD and animal models of autism described abnormal matrix:striosome volume ratios, with an possible shift from striosome to matrix volume. Shifting the matrix:striosome ratio could result from expansion in matrix, reduction in striosome, spatial redistribution of the compartments, or a combination of these changes. Each type of ratio-shifting abnormality may predispose to ASD but yield different combinations of ASD features. \n\nMethods: We developed a cohort of 426 children and adults (213 matched ASD-control pairs) and \nperformed connectivity-based parcellation (diffusion tractography) of the striatum. This identified voxels with matrix-like and striosome-like patterns of structural connectivity. \n\nResults: Matrix-like volume was increased in ASD, with no evident change in the volume or organization of the striosome-like compartment. The inter-compartment volume difference (matrix minus striosome) within each individual was 31% larger in ASD. Matrix-like volume was increased in both caudate and putamen, and in somatotopic zones throughout the rostral-caudal extent of the striatum. Subjects with moderate elevations in ADOS (Autism Diagnostic Observation Schedule) scores had increased matrix-like volume, but those with highly elevated ADOS scores had 3.7-fold larger increases in matrix-like volume.\n\nConclusions: Matrix and striosome are embedded in distinct structural and functional networks, suggesting that compartment-selective injury or maldevelopment may mediate specific and distinct clinical features. Previously, assessing the striatal compartments in humans required post mortem tissue. Striatal parcellation provides a means to assess neuropsychiatric diseases for compartment-specific abnormalities in vivo. While this ASD cohort had increased matrix-like volume, other mechanisms that shift the matrix:striosome ratio may also increase the chance of developing the diverse social, sensory, and motor phenotypes of ASD.\n","doi":"10.15154/khn8-jf08","id":3094,"state":"Shared","study_subject_count":2166,"title":"The striatal matrix compartment is expanded in autism spectrum disorder."},{"collection_subject_count":11,"data_usage":"Secondary Analysis","description":"Previous diffusion magnetic resonance imaging (dMRI) research has indicated altered white matter microstructure in autism, but the implicated regions are inconsistent across studies. Such prior work has largely used conventional dMRI analysis methods, including the traditional microstructure model, diffusion tensor imaging (DTI). However, these methods are limited in their ability to precisely map microstructural differences and accurately resolve complex fiber configurations. In our study, we investigated white matter microstructure alterations in autism using the refined along-tract analytic approach, BUndle ANalytics (BUAN), with both an advanced microstructure model, the tensor distribution function (TDF) and DTI. We analyzed dMRI data from 365 autistic and neurotypical participants (5-24 years; 34% female) from 10 cohorts to examine commissural and association tracts. Autism was associated with lower fractional anisotropy and higher diffusivity in localized portions of nearly every commissural and association tract examined; these tracts inter-connected a wide range of brain regions, including frontal, temporal, parietal, and occipital regions. Taken together, BUAN and TDF allow robust and spatially precise mapping of microstructural properties in autism. Our findings rigorously demonstrate that white matter microstructure alterations in autism may be greater within specific regions of individual tracts, and that the implicated tracts are distributed across the brain.","doi":"10.15154/91w9-gc71","id":2840,"state":"Shared","study_subject_count":259,"title":"Mapping Along-Tract Commissural and Association White Matter Microstructural Differences in Autistic Children and Young Adults"},{"collection_subject_count":51,"data_usage":"Primary Analysis","description":"The relationship between brain development and clinical heterogeneity in autism (ASD) is unknown. This study examines the Social Responsiveness Scale (SRS) in relation to the longitudinal development of cortical thickness. Participants (N = 91 ASD, N = 56 TDC; 3-39 years at first scan) were scanned up to three times over a 7-year period. Mixed-effects models examined cortical thickness in relation to SRS score. ASD participants with higher SRS scores showed regionally increased age-related cortical thinning. Regional thickness differences and reduced age-related cortical thinning were found in predominantly right lateralized regions in ASD with decreasing SRS scores over time. Our findings emphasize the importance of examining clinical phenotypes in brain-based studies of ASD.","doi":"10.5072/1358260","id":563,"state":"Shared","study_subject_count":133,"title":"Social Responsiveness Scale (SRS) in Relation to Longitudinal Cortical Thickness Changes in Autism Spectrum Disorder."},{"collection_subject_count":90,"data_usage":"Primary Analysis","description":"Importance: Despite reports of widespread but heterogenous atypicality of functional connectivity in individuals with autism, little is known regarding the temporal dynamics of functional brain connections and how this relates to autistic traits.\r\nObjective: To investigate differences in temporal synchrony between brain regions in individuals with autism and typical development.\r\nDesign: Cohort and replication sample study. The cohort includes data acquired between December 2016 and April 2018. Aggregate data included in the replication sample were released to the public in August 2012 (ABIDE I) and June 2016 (ABIDE II). Data were analyzed in April 2018. \r\nSetting: Population-based study conducted at the University of Utah.\r\nParticipants: This cohort study, conducted at the University of Utah, included 90 adolescent and adult male participants. A larger sample from the multisite Autism Brain Imaging Data Exchange (ABIDE) was also used as a replication sample. \r\nMain Outcomes and Measures: Long duration (30 minutes per subject) of multiband, multi-echo functional magnetic resonance imaging was acquired in order to estimate functional connectivity between brain regions. Sustained connectivity, a measure of functional connectivity duration, as well as lagged temporal dynamics related to functional connectivity, were compared between groups for 361 gray matter regions of interest and a 17-network parcellation. Lagged findings were replicated in the larger ABIDE sample (n=1402). Sustained connectivity findings were also associated with behavioral and cognitive variables.\r\nResults: In 52 individuals with autism (mean [SD] age, 27.73 [8.66] years) and 38 controls (mean [SD] age, 27.09 [7.49] years), increases in both sustained connectivity and functional connectivity at several lags were found in individuals with autism compared to controls. Group differences in functional connectivity were replicated in the larger ABIDE dataset at a six second lag. Measures of symptom severity in individuals with autism were positively associated with sustained connectivity values. In controls, sustained connectivity was negatively associated with cognitive processing.\r\nConclusions and Relevance: Whereas the magnitude of functional connectivity in autism is variable across brain regions, participant samples, and development, prolonged temporal synchrony of functional connections is reproducibly observed in autism, suggesting a potential mechanism for core symptoms. ","doi":"10.15154/1475202","id":614,"state":"Shared","study_subject_count":90,"title":"Evaluation of Differences in Temporal Synchrony Between Brain Regions in Individuals With Autism and Typical Development"}]